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Impact of KCNQ1, CDKN2A/2B, CDKAL1, HHEX, MTNR1B

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Impact of KCNQ1, CDKN2A/2B, CDKAL1, HHEX, MTNR1B Plengvidhya et al. BMC Medical Genetics (2018) 19:93 https://doi.org/10.1186/s12881-018-0614-9 RESEARCH ARTICLE Open Access Impact of KCNQ1, CDKN2A/2B, CDKAL1, HHEX, MTNR1B, SLC30A8, TCF7L2, and UBE2E2 on risk of developing type 2 diabetes in Thai population Nattachet Plengvidhya1, Chutima Chanprasert1,2, Nalinee Chongjaroen3, Pa-thai Yenchitsomanus4, Mayuree Homsanit5 and Watip Tangjittipokin3* Abstract Background: Several type 2 diabetes (T2D) susceptibility loci identified via genome-wide association studies were found to be replicated among various populations. However, the influence of these loci on T2D in Thai population is unknown. The aim of this study was to investigate the influence of eight single nucleotide polymorphisms (SNPs) reported in GWA studies on T2D and related quantitative traits in Thai population. Methods: Eight SNPs in or near the KCNQ1, CDKN2A/2B, SLC30A8, HHEX, CDKAL1, TCF7L2, MTNR1B, and UBE2E2 genes were genotyped. A case-control association study comprising 500 Thai patients with T2D and 500 ethnically- matched control subjects was conducted. Associations between SNPs and T2D were examined by logistic regression analysis. The impact of these SNPs on quantitative traits was examined by linear regression among case and control subjects. Results: Five SNPs in KCNQ1 (rs2237892), CDK2A/2B (rs108116610, SLC30A8 (rs13266634), TCF7L2 (rs7903146) and MTNR1B (rs1387153) were found to be marginally associated with risk of developing T2D, with odds ratios ranging from 1.43 to 2.02 (p = 0.047 to 3.0 × 10–4) with adjustments for age, sex, and body mass index. Interestingly, SNP rs13266634 of SLC30A8 gene reached statistical significance after correcting for multiple testing (p = 0.0003) (p <0. 006 after Bonferroni correction). However, no significant association was detected between HHEX (rs1111875), CDKAL1 (rs7756992), or UBE2E2 (rs7612463) and T2D. We also observed association between rs10811661 and both waist circumference and waist-hip ratio (p = 0.007 and p = 0.023, respectively). In addition, rs13266634 in SLC30A8 was associated with glycated hemoglobin (p = 0.018), and rs7903146 in TCF7L2 was associated with high-density lipoprotein cholesterol level (p = 0.023). Conclusion: Of the eight genes included in our analysis, significant association was observed between KCNQ1, CDKN2A/2B, SLC30A8, TCF7L2, and MTNR1B loci and T2D in our Thai study population. Of these, CDKN2A/2B, SLC30A8, and TCF7L2 genes were also significantly associated with anthropometric, glycemic and lipid characteristics. Larger cohort studies and meta-analyses are needed to further confirm the effect of these variants in Thai population. Keywords: Type 2 diabetes, Association study, Single nucleotide polymorphisms, Thai population, Genome-wide association study * Correspondence: [email protected] 3Department of Immunology, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok, Thailand Full list of author information is available at the end of the article © The Author(s). 2018 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. Plengvidhya et al. BMC Medical Genetics (2018) 19:93 Page 2 of 9 Background and C2CD4A-C2CD4B were reported to be associated The prevalence of diabetes, especially type 2 diabetes with T2D by two relatively small East Asian GWA studies, (T2D), continues to increase worldwide. The Inter- while these loci did not reach genome-wide significance in national Diabetes Federation (IDF) has estimated that European studies [4, 5, 14]. Furthermore, there are rela- the prevalence of diabetes will increase from 451 million tively large frequency differences between population in 2017 to 693 million by 2045 [1]. The number of groups for rs7903146 within TCF7L2 [15]. Although nu- people with diabetes will increase as a result of changes merous T2D risk loci were identified from GWA studies in lifestyle caused by urbanization, high population in multi-ethnic populations, the functional impact of these growth, ageing population, and high economic growth. risk loci still needs to be elucidated. Most of these risk loci In 2017, the prevalence of diabetes among adults in likely affect insulin secretion and beta-cell function, with a Thailand was estimated to be 8.3% [1]. T2D is a complex few potentially involved in insulin action. Given this vari- and multifactorial disease that is characterized by im- ability among populations, it is important that we under- paired insulin secretion and insulin resistance [2, 3]. stand the association between genetic variations and T2D, T2D is associated with significant morbidity and mortal- and the roles of these T2D risk loci in Thai population. In ity, especially decreased life expectancy and reduced this study, we investigated single nucleotide polymor- quality of life, as well as high cost of treatment and re- phisms (SNPs) that were previously found to be asso- duced productivity. Although the etiology of T2D is not ciated with T2D in Asian populations. We focused on thoroughly understood, genetic and environmental fac- the following eight SNPs: 1) potassium voltage-gated tors are thought to be involved in the pathogenesis of channel, KQT-like subfamily, member 1 (KCNQ1; this disease. rs2237892); 2) a variant found near cyclin-dependent Prior to the development of currently available methods kinase inhibitor 2A (CDKN2A/2B; rs10811661); 3) a and technologies, linkage and candidate gene association zinc transporter member of solute carrier family 30 studies were conducted; however, these two methods (SLC30A8; rs13266634); 4) hematopoietically-expressed could identify only a few genes involved in the pathogen- homeobox (HHEX; rs1111875); 5) CDK5 regulatory esis of T2D (i.e., PPARG, KCNJ11, CAPN10,andTCF7L2). subunit-associated protein 1-like 1 (CDKAL1; rs7756992); Advances in genotyping technology and genetic informa- 6) melatonin receptor type 1B (MTNR1B; rs1387153); 7) tion have facilitated the application of genome-wide asso- transcription factor-7-like 2 (TCF7L2; rs7903146); and, 8) ciation (GWA) studies to identify T2D susceptibility Ubiquitin Conjugating Enzyme E2 E2 (UBE2E2; genes. Currently, over 120 common risk variants have rs7612463). Our specific aim was to investigate the influ- been successfully identified as being associated with T2D ence of these eight SNPs on T2D and related quantitative using this approach [4–12]. Several reproducible GWA traits in Thai population. studies confirmed these well-established susceptibility genes, and they were found to be replicated for association Methods with T2D and diabetes-related traits in or near SLC30A8, Study subjects KCNQ1, CDC123, HNF1B, KCNJ11, TCF7L2, CDKAL1, A total of 1000 individuals, including 500 Thai T2D CDKN2A/2B, PPARG, HHEX, IGF2BP2, GLIS3, JAZF1, patients and 500 ethnically-matched control subjects WFS1, and MTNR1B in Europeans and East Asians. Most were enrolled during the 2005 to 2015 study period. of the susceptibility risk loci identified were shared among T2D patients were recruited at the Siriraj Diabetes East Asians and populations with Europeans ancestry. Center, Department of Endocrinology and Metabolism, However, significant association signals at these shared Faculty of Medicine Siriraj Hospital, Mahidol University, loci seems to be independent among populations. This Bangkok, Thailand. Siriraj Hospital is Thailand’s largest suggests that the pathogenesis of the disease is common national tertiary referral center. Diabetes was diagnosed among populations, but that risk variants are often popu- based on American Diabetes Association (ADA) criteria lation specific. These differences in risk variants between [3]. Control subjects consisted of 500 individuals without Europeans and East Asians are likely due to differences in diabetes who were enrolled from the Health Check-up genetic background, risk allele frequencies, and character- Center of the Department of Preventive and Social istics, such as body shape, food and drink, culture, and Medicine, Faculty of Medicine Siriraj Hospital, Mahidol other lifestyle factors. For example, association of var- University. Healthy controls had to satisfy all of the iants within KCNQ1 [6, 13] was primarily reported in following inclusion criteria: age > 40 years, no family GWA studies in East Asians; however, these variants history of diabetes in any first-degree relatives, fasting were not identified in any of the larger GWA studies plasma glucose < 100 mg/dl (6.1 mmol/l), and HbA1c in European populations, because there are different < 5.7%. Written informed consent was obtained from all frequencies of these variants between East Asian and participants after a full explanation of the study’s pur- European populations. Similarly, variants within UBE2E2 pose and protocol. The study protocol and informed Plengvidhya et al. BMC Medical Genetics (2018) 19:93 Page 3 of 9 consent procedures were approved by the Siriraj Institu- at a rate of 25 acquisitions per one degree Celcius. Quality tional Review Board (SIRB), Faculty of Medicine
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